Kristian Bodolai's repositories
cleanlab
The standard package for machine learning with noisy labels and finding mislabeled data in Python.
codecarbon
Track emissions from Compute and recommend ways to reduce their impact on the environment.
cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
earthengine-community
Tutorials and content created by Earth Engine users, for Earth Engine users
eo-satellites
Register and create databases of EO satellites and products
fastai
The fastai deep learning library
fastbook
The fastai book, published as Jupyter Notebooks
forestatrisk
:package: :snake: Python package to model and forecast the risk of deforestation
GEDI-BDL
This repository provides the code used to create the results presented in "Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles".
iris
Semi-automatic tool for manual segmentation of multi-spectral and geo-spatial imagery.
lidR
Airborne LiDAR data manipulation and visualisation for forestry application
nbdev
Create delightful python projects using Jupyter Notebooks
OpenSarToolkit
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language.
phileo-bench
Repo for testing foundation models
pigeon
🐦 Quickly annotate data from the comfort of your Jupyter notebook
planetary-computer-containers
Container definitions for the Planetary Computer
python-ecosia-images
Python module for searching and downloading images from Ecosia
Rbeast
Bayesian Change-Point Detection and Time Series Decomposition
SatelliteVu-AWS-Disaster-Response-Hackathon
Satellite Vu submission for the AWS Disaster Response hackathon
setup
Tools for setting up remote servers
tanintharyi
Google Earth Engine code for land classification in Tanintharyi, Myanmar
temporalCNN
Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series
tsai
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai